Correlation Clustering is a clustering cost function that partitions a graph with positive and negative edge weights. The cost function sums the disagreements, i.e., the sum of negative intra-cluster edge weights plus the sum of positive inter-cluster edge weights. The respective cost function on general graphs is defined by [1]}
\(R^{CC}(c,\mathbf {X}) = \sum _{(i,j) \in E^{<+>}} \mathbf {X}_{ij}(1-\mathbf {H}_{ij}) - \sum _{(i,j) \in E^{<->}} \mathbf {X}_{ij} \mathbf {H}_{ij} \, ,\) 
